What’s Hot in Intelligent User Interfaces

Authors: Shimei Pan, Oliver Brdiczka, Giuseppe Carenini, Duen Chau, Per Ola Kristensson

AAAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical Here we summarize the latest trends in IUI based on our experience organizing the 20th ACM IUI Conference in Atlanta in 2015. The paper describes trends and challenges in the field of Intelligent User Interfaces based on the authors' experience and survey of other works, rather than conducting new empirical studies, data analysis, or validating hypotheses of its own.
Researcher Affiliation Collaboration Shimei Pan University of Maryland, Baltimore County Baltimore, MD 21250, USA; Oliver Brdiczka Vectra Networks San Jose, CA 95128, USA; Giuseppe Carenini University of British Columbia Vancouver, BC V6T 1Z4, Canada; Duen Horng Chau Georgia Institute of Technology Atlanta, GA 30332, USA; Per Ola Kristensson University of Cambridge Cambridge CB2 1TN, UK
Pseudocode No The paper does not contain any pseudocode or algorithm blocks.
Open Source Code No The paper is a survey and trend summary, and it does not present a new method or system developed by the authors for which source code would be provided.
Open Datasets No The paper is a survey and does not present new experimental work by the authors, therefore it does not use or provide access information for a public dataset for its own research.
Dataset Splits No The paper is a survey and does not present new experimental work by the authors, thus it does not provide details on training, validation, or test dataset splits.
Hardware Specification No The paper is a survey and does not describe experiments performed by the authors, thus no specific hardware specifications are provided.
Software Dependencies No The paper is a survey and does not describe its own technical implementation requiring specific software dependencies with version numbers.
Experiment Setup No The paper is a survey and does not describe its own experimental setup or provide hyperparameter values and training configurations.